When OpenAI launched ChatGPT in November 2022, debates about artificial intelligence (AI) shifted from technical capability to societal consequences. Three years on, AI systems trained on vast datasets are moving into cognitive work across sectors with almost minimal adaptation, reshaping professional roles and career trajectories.

Public discussion of this issue has settled into two familiar camps. One warns of displacement and instability. The other predicts productivity gains and rapid economic growth. What both positions have in common is a focus on the future.

The central question for liberal democracies, however, is not whether AI will reshape labor markets, but whether today’s political systems have the institutional capacity to govern a transition that is already underway without eroding the social contract that underpins democratic consent.

The EU has sought to establish guardrails through its AI Act. That intervention matters, but regulating how systems are developed and deployed is distinct from managing how societies absorb the structural economic changes that will result. If AI marks a sustained reorganization of work, then Europe’s response must extend beyond regulating these new systems by moving into fiscal planning and institutional redesign.

As policymakers gather this week at the AI Impact Summit in India, similar questions about productivity and inclusion are being debated at a global scale, with changes to the workforce prioritized by many delegates.

What is required alongside the AI Act is a dedicated European labor transition framework, ideally embedded in the bloc’s 2028–2034 budget. A ring-fenced line for AI-driven labor adjustment would recognize that this shift is structural rather than temporary. The purpose is not simply to mitigate visible disruption, but to anticipate and shape how labor markets will evolve over time.

A credible response rests on three pillars: establishing social protections for displaced workers, providing training infrastructure scaled for continuous transition, and working to build public trust.

AI disruption is unlikely to manifest as sudden mass redundancy. It is more likely to take the form of incremental task substitution and workflow automation that progressively reduce the scope of existing roles. Jobs would be hollowed out before being eliminated, creating prolonged insecurity rather than immediate unemployment.

In 2025, the German Institute for Employment Research projected that 1.6 million jobs could be reshaped by—or lost to—AI in Germany alone over the next fifteen years. The report warned that certain economic sectors “will experience an increase in labor demand, while others face a decline in employment.” Another analysis found that women are almost twice as likely as men to be working in a job that has high exposure to AI.

Social protection systems built around stable long-term employment are poorly calibrated for this pattern of gradual erosion. As a starting point, Europe needs social benefits that apply across member states and employment categories, as well as faster access to retraining support.

The second pillar is skills and workforce infrastructure. Evidence from more than 12,000 European firms shows that adopting AI increases productivity by around 4 percent on average, with no immediate employment losses. However, these gains depend heavily on complementary investment, particularly in workforce training. Productivity improvements do not materialize automatically, they are reinforced through deliberate investment in human capital.

Europe should expand sector-specific transition funds, strengthen youth employment programs and create structured mid-career conversion pathways for workers in exposed professions. Domain expertise will remain valuable, albeit increasingly in combination with AI literacy and integration skills.

The third pillar is trust. Democratic stability depends less on aggregate employment statistics than on whether citizens believe that the AI transition is being managed fairly and competently. Earlier industrial revolutions unfolded over decades. And while the computer age enhanced productivity by accelerating human tasks, it did not systematically replace cognitive labor at scale. By contrast, AI systems can draft, analyze, code, and advise across professional domains once considered insulated from automation.

This transition is also unfolding in a more fragile political environment, shaped by digital disinformation, polarization, and declining institutional confidence. Adjustment shocks are therefore more likely to be amplified and politicized. If citizens perceive that the benefits of this transition are felt by the few while its drawbacks fall on the many, institutional legitimacy will weaken.

Building public trust must therefore be an explicit objective of transition policy. Workers need confidence that the AI systems affecting their livelihoods can operate transparently and fairly. Citizens need evidence that governments are steering structural change through sustained fiscal commitment rather than reacting to its consequences.

AI presents a real opportunity for higher productivity, new forms of work, and expanded access to knowledge. New roles will be created, and access to careers once restricted by geography and formal qualifications will be enhanced. However, great opportunity does not neutralize political risk. Without visible, resourced, and forward-looking transition policy embedded in Europe’s fiscal framework, technological progress may deepen social and political strain.

Governing this transition will be the ultimate test of democratic resilience at the dawn of a new age.

Amanda Coakley is a Europe’s futures fellow at the Institute for Human Sciences (IWM) in Vienna and a fellow in the AI Safety Initiative at Georgia Institute of Technology.

This publication is part of EU Cyber Direct – EU Cyber Diplomacy Initiative’s New Tech in Review, a collection of commentaries that highlights key issues at the intersection of emerging technologies, cybersecurity, defense, and norms.